GOALI: Intelligent Systems for Health Condition Prognostics in AC Permanent Magnet and Induction Machine Drives for Highly Efficient and Renewable Energy Utilization and Generation

GOALI：用于交流永磁和感应电机驱动健康状况预测的智能系统，以实现高效和可再生能源的利用和发电

• 批准号: 1028348
• 负责人: Nabeel Demerdash
• 金额: $ 42.5万
• 依托单位: Marquette University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-09-15 至 2015-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1028348&HistoricalAwards=false
• 关键词: GOALI; Intelligent; Systems; Health; Condition

Intellectual MeritMost electric drives are currently employing induction machines in variable speed drives to reduce electric energy consumption. Latest hybrid vehicles, direct-drive wind turbine-generators and ultra-high efficiency heating and air-conditioning equipment employ brushless permanent magnet (BLPM) machine-drives for higher energy efficiency. Wider penetration of this technology requires an in-depth understanding of the fault mechanisms for developing fault prognostics and mitigation methods and robust fault tolerant designs.Both ac BLPM synchronous and induction machines, referred to as ac machines, will be studied in this project. The objectives of this research are:1. Develop novel fault diagnostic methods in ac machine-drives,2. Discover novel nonlinear-estimation methods for prognosis of the useful life of ac machine-drives,3. Discover techniques for fault mitigation in ac machine-drives to include a combination of adaptive control algorithms and novel fault-tolerant system topologies.Broader ImpactThe main benefits of this research are the development of fault prognostics and mitigation technologies for high efficiency ac machine-drives that the industrial partner, which is one of the largest electric machine manufacturers in North America, is well positioned to introduce into the market through a multitude of Original Equipment Manufacturers that it serves. The liaison between University and Industry will be enhanced by including reciprocal long term working visits and internships of faculty, students and engineers. The research results will be integrated into the graduate and undergraduate curricula. Under-represented groups will be targeted for participation. The results will be disseminated to the wider engineering community through professional journals and conferences.

智能优点目前，大多数电力驱动器都采用感应电机的变速驱动器，以减少电能消耗。最新的混合动力汽车、直驱风力涡轮发电机和超高效供暖和空调设备采用无刷永磁（BLPM）机器驱动器，以实现更高的能效。更广泛地渗透这一技术需要深入了解故障机理，以开发故障诊断和缓解方法以及鲁棒的容错设计。交流BLPM同步和感应电机（简称交流电机）将在本项目中进行研究。本研究的目的是：1.开发交流电机驱动器的新型故障诊断方法。发现新的非线性估计方法预测交流电机驱动器的使用寿命，3。发现交流电机驱动器中的故障缓解技术，包括自适应控制算法和新型容错系统拓扑结构的组合。更广泛的影响这项研究的主要好处是为高效率交流电机驱动器开发故障诊断和缓解技术，工业合作伙伴是北美最大的电机制造商之一，通过它所服务的众多原始设备制造商将其引入市场。大学和工业界之间的联系将通过包括教师、学生和工程师的长期工作访问和实习来加强。研究成果将纳入研究生和本科生课程。代表性不足的群体将成为参与的对象。研究结果将通过专业期刊和会议向更广泛的工程界传播。